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What Drives Mortality Among HIV Patients in a Conflict Setting?

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What Drives Mortality Among HIV Patients in a Conflict Setting? Crellen et al. Conflict and Health (2019) 13:52 https://doi.org/10.1186/s13031-019-0236-7 RESEARCH Open Access What drives mortality among HIV patients in a conflict setting? A prospective cohort study in the Central African Republic Thomas Crellen1,2* , Charles Ssonko3,TuridPiening4, Marcel Mbeko Simaleko5, Karen Geiger1 and M. Ruby Siddiqui3 Abstract Background: Provision of antiretroviral therapy (ART) in conflict settings is rarely attempted and little is known about the expected patterns of mortality. The Central African Republic (CAR) continues to have a low coverage of ART despite an estimated 110,000 people living with HIV and 5000 AIDS-related deaths in 2018. We present results from a cohort in Zemio, Haut-Mboumou prefecture. This region had the highest prevalence of HIV nationally (14.8% in a 2010 survey), and was subject to repeated attacks by armed groups on civilians during the observed period. Methods: Conflict from armed groups can impact cohort mortality rates i) directly if HIV patients are victims of armed conflict, or ii) indirectly if population displacement or fear of movement reduces access to ART. Using monthly counts of civilian deaths, injuries and abductions, we estimated the impact of the conflict on patient mortality. We also determined patient-level risk factors for mortality and how the risk of mortality varies with time spent in the cohort. Model-fitting was performed in a Bayesian framework, using logistic regression with terms accounting for temporal autocorrelation. Results: Patients were recruited and observed in the HIV treatment program from October 2011 to May 2017. Overall 1631 patients were enrolled and 1628 were included in the analysis giving 48,430 person-months at risk and 145 deaths. The crude survival rate after 12 months was 0.92 (95% CI 0.90, 0.93). Our model showed that patient mortality did not increase during periods of heightened conflict; the odds ratios (OR) 95% credible interval (CrI) for i) civilian fatalities and injuries, and ii) civilian abductions on patient mortality both spanned unity. The risk of mortality for individual patients was highest in the second month after entering the cohort, and declined seven- fold over the first 12 months. Male sex was associated with a higher mortality (odds ratio 1.70 [95% CrI 1.20, 2.33]) along with the severity of opportunistic infections (OIs) at baseline (OR 2.52; 95% CrI 2.01, 3.23 for stage 2 OIs compared with stage 1). Conclusions: Our results show that chronic conflict did not appear to adversely affect rates of mortality in this cohort, and that mortality was driven predominantly by patient-specific risk factors. The risk of mortality and recovery of CD4 T-cell counts observed in this conflict setting are comparable to those in stable resource poor settings, suggesting that conflict should not be a barrier in access to ART. Keywords: Antiretroviral therapy, Conflict setting, Survival analysis, Cohort study, Central African Republic * Correspondence: [email protected] 1Médecins Sans Frontières Hollande, Avenue Barthelemy Boganda, PK4, Bangui, BP 1793, Central African Republic 2Mahidol-Oxford Tropical Medicine Research Unit, 420/6 Rajvithi Road, Tungphyathai, Bangkok 10400, Thailand Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Crellen et al. Conflict and Health (2019) 13:52 Page 2 of 11 Introduction up (LTFU) of patients on ART in conflict settings after 12 Sub-Saharan Africa (SSA) exhibits disproportionate levels months was 9.0 and 8.1% respectively, which are within of morbidity and mortality from both infectious diseases the range of mortality and LTFU estimates from non- and conflict. Despite SSA accounting for 14.2% of the conflict settings [19]. world’spopulation[1], estimates by UNAIDS for 2018 The Central African Republic (CAR) is one of the gave the numbers of people living with HIV (PLHIV) in world’s least developed nations [20] and faces a number SSA at 25.6 million and AIDS-related deaths at 470,000; of challenges in healthcare provision including disrup- representing 67.5 and 61.0% respectively of the global to- tion of services due to instability and civil conflict along tals [2]. The Uppsala Conflict Data Program reported 20 with a lack of infrastructure, particularly outside of the separate conflicts in SSA in 2018; the African region had capital Bangui. At the onset of the study taking place, the highest number of fatalities from non-state conflicts CAR had an estimated 120,000 PLHIV and 11,000 (5408; 45.7%) and attacks against civilians (2888; 70.0%) AIDS-related deaths in 2013 [21] giving a mortality rate [3]. This is consistent with the disproportionate levels of of 91 deaths per 1000 PLHIV annually, which was the violent conflict in SSA since 2010 [4, 5]. Examples of re- highest in the world [22]. More recent estimates by gions in SSA with a dual burden of HIV and conflict in UNAIDS for 2018 suggest there are 110,000 PLHIV in 2018 include South Sudan, which had a national adult CAR (uncertainty interval [UI] 90,000 – 140,000) and prevalence of 2.5% in 2018 [2]thoughhigherestimates 4800 AIDS-related deaths (UI 3700 – 6400) [2]. In 2018, (3.1–6.8%) in conflict affected southern states [6], the it was estimated that 36% (UI 30–45%) of people living Cabo Delgado province of northern Mozambique which with HIV were receiving ART [2]. was subject to attacks by Islamic extremists in 2018 and MSF conducted a nationwide HIV seroprevalence study had a HIV prevalence of 12.6% in the same year [2], and in 2010 which found the Haut-Mbomou prefecture to Maniema province of the eastern Democratic Republic of have the highest prevalence in CAR; 14.8% compared with Congo, which saw clashes between government forces and a prevalence of 5.9% nationally among individuals 15–49 rebel groups in 2018, had an estimated HIV prevalence of years of age [23]. Access to treatment in CAR was particu- 3.4% compared with a national average of 1.0% [7]. larly low at this time, 13.8% in 2010 [21]. The health Nations in SSA affected by conflict have been shown to centre in Zemio, Haut-Mboumou prefecture has been have worse health outcomes, such as rates of mortality for supported by MSF since 2010 and an ART cohort was mothers and children under-five [8, 9]. The relationship be- established in October 2011. This was initially a response tween conflict and the transmission of infectious disease is to an influx of Congolese refugees and internally displaced more complex and contested in the literature. Conflict in persons (IDPs), who had fled their homes due to repeated SSA between 1997 and 2010 did not appear to result in attacks by the Lord’s Resistance Army (LRA) during higher transmission rates for falciparum malaria and the 2008–10. The region has since faced repeated violent in- pre-conflict trend was generally maintained [10]. For HIV, cursions from armed groups [24]. The Zemio HIV treat- a number of multi-site studies in SSA have argued there is ment program therefore represented an attempt to no evidence that infection incidence increases during con- provide access to ART for a population with a high disease flict when compared with pre-conflict rates [11–13]. How- burden in a conflict setting. ever, a cohort study of police officers in Guinea-Bissau Reports of HIV patient outcomes generally focus on during the 1998–9 civil war reached the opposite conclu- summary statistics after defined intervals (6 or 12 sion for the incidence of HIV-1 [14], and the observations months) and are rarely explored as a detailed time series. of stable or decreasing HIV incidence before and during It is important to consider temporal variation in patient conflict from cross-sectional surveys could be confounded mortality as this has implications for management of pa- by higher rates of, unobserved, AIDS-related mortality [15]. tient care and allocation of resources during ART pro- Provision of anti-retroviral therapy (ART) during con- grams. For instance, the risk of mortality among patients flict has, historically, not been prioritised due to a percep- in sub-Saharan Africa is particularly high in the first 3 tion that this was too difficult to achieve [16]. In the face months of ART provision [25, 26] due to individuals of long term conflicts in areas with a high HIV burden, seeking treatment at a later stage of disease progression there was concern in the humanitarian community that [27]. In the case of studies on the impact of conflict, lon- “treatment cannot wait” [13, 17]. In 2010 the medical or- gitudinal data is particularly important as instability is ganisation Médecins Sans Frontières (MSF) reported re- rarely temporally uniform and often consists of periods sults from 22 ART programs in conflict or post-conflict of relative calm punctuated by acute violence [17]. Con- settings in SSA, finding that patient outcomes were com- flict from armed groups can impact mortality rates i) parable to those in stable resource-limited settings [18]. directly if HIV patients are victims of armed conflict, or These findings were also shown in a systematic review ii) indirectly if population displacement or fear of move- and meta-analysis that found mortality and loss to follow- ment reduces adherence to ART [28].
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